Engineering Trust for the Algorithmic Age of Medicine.

Healthcare is deploying black-box intelligence into life-or-death decisions, yet the foundational layer of verifiable trust remains missing.

Verivis Lab engineers the cryptographic and decentralized protocols required to make medical AI auditable, accountable, and worthy of clinical trust.

Verivis Projects

Verivis Project • Invisible Risk Trust Framework

Whitepaper Released • 2026

Decentralized, privacy-preserving validation layer for medical AI using ZKPs and distributed expert consensus.

Verivis Project • Proof of Inference (PoI) Protocol

Active • In-Silico Validated

Per-inference cryptographic attestation using zk-SNARKs (Groth16).

Verivis Project • Clinical Model Autophagy

Active In-Silico • Target: May 2026

Developing the "Data Purity Standard (DPS)" to prevent interpretative drift in hospital LLM systems.

2026–2027 Roadmap

Q1 2026

Verivis Lab Public Launch
Website • Whitepapers • GitHub

Q2 2026

PoI Protocol Open Source
Reference implementation + SDK

Q3 2026

First Hospital Pilot
Taiwan multi-center PSMA PET/CT validation

Q4 2026 – 2027

Verivis DAO + Certification Layer
"Verivis Certified" medical AI standard

Let's Build the Future of Trustworthy Medical AI Together

We are actively seeking strategic collaborators — hospitals, AI research groups, pharmaceutical companies, DeSci builders, and forward-thinking regulators who understand that verifiable trust is the missing foundation for clinical AI adoption.

Whether you bring real-world clinical data, regulatory expertise, compute resources, or simply share our vision — we want to hear from you.

Start a Conversation with Peter Shih, MD →